class_docstr: Interface of recurrent and stateful models.
  
  This is an interface of recurrent and stateful models. ChainerRL supports
  recurrent neural network models as stateful models that implement this
  interface.
  
  To implement this interface, you need to implement three abstract methods
  of it: get_state, set_state and reset_state.
code: def push_state(self):
      self.__state_stack.append(self.get_state())
      self.reset_state()
  
imports: from abc import ABCMeta
  from abc import abstractmethod
  import collections
  import contextlib
  import chainer
label_desc: Use image node_id 5 for calling the Recurrent obj's underlying member method code with example usage: obj.push_state() without return types